Abstract The purpose of this study is to determine whether quantitative, multiparametric breast MRI performed prior to biopsy can biologically characterize a common pre-invasive malignancy, ductal carcinoma in situ (DCIS), which typically presents in asymptomatic women as suspicious calcifications on mammography. Unfortunately, the appearance of these calcifications cannot distinguish DCIS from benign breast pathology, and current pathologic tests cannot reliably distinguish clinically important forms of DCIS from those that behave indolently. This leads to unnecessary biopsies and therapies, including surgeries and radiation treatment. Recent advanced pathologic and multigene assays of DCIS and its microenvironment hold promise for improved risk assessments but have limited validation to date and are prone to sampling error due to lesion heterogeneity. Our prior studies support the use of quantitative MRI measurements of vascular permeability (Ktrans, signal enhancement ratio [SER]), cellular density (apparent diffusion coefficient [ADC] and tissue diffusion [Dt]), and microperfusion (perfusion fraction [?]) to characterize DCIS biology. We hypothesize that the use of these quantitative MRI features will provide an accurate, non-invasive biological risk assessment of DCIS lesions. To test this hypothesis, we will assess whether quantitative MRI markers of vascular permeability and cellularity can accurately exclude the presence of DCIS-associated malignancy and whether more advanced MRI markers of biology can further distinguish between aggressive from less aggressive forms of DCIS in a prospective observational clinical trial of 150 women presenting with suspicious mammographic calcifications at the University of Washington. All participants will undergo a pre-biopsy, 3 tesla high spatiotemporal resolution dynamic contrast enhanced and multi-b value reduced field of view diffusion weighted breast MRI. Quantitative MRI features, including SER, Ktrans, ADC, Dt, and ?, will be measured for each lesion and the surrounding (peri-tumoral) stroma. We will assess whether these MRI signatures can determine which calcifications identified as suspicious on mammography actually harbor DCIS, and whether these imaging features correlate with pathologic markers of proliferation (Ki-67) and inflammation (cox-2) within DCIS lesions. We will also explore whether these quantitative MRI features in the peri-tumoral region correlate with prognostic microenvironment markers of inflammation (TNF?) and angiogenesis (VEGF). Finally, we will assess whether a multivariate model using these markers can accurately predict risk of recurrence based on a multi-gene assay (Oncotype DX DCIS score). If successful, this study could lead to larger clinical trials that use MRI features to 1) decrease unnecessary biopsies of calcifications that in fact represent benign pathology and 2) provide accurate assessments of DCIS risk of progression to invasive disease and recurrence after treatment that could help facilitate individualized and targeted therapies. This will address an important public health goal: decreasing overdiagnosis and overtreatment of early breast cancer.